Establishment and validation of the quantitative analysis of multi‐components by single marker for the quality control of Qishen Yiqi dripping pills by high‐performance liquid chromatography with charged aerosol detection

Abstract Introduction Charged aerosol detection (CAD) has the merits of high sensitivity, high universality and response uniformity. The strategy that combines the quantitative analysis of multi‐components by single marker (QAMS) with CAD has certain advantages for the quantification of multi‐components. However, relevant research was limited. Objectives To comprehensively investigate the crucial factors that affect the performance of the HPLC‐CAD‐QAMS approach and validate the credibility and feasibility of the method. Methodology Multiple components of Qishen Yiqi dripping pills (QSYQ) were assayed using the high‐performance liquid chromatography (HPLC)‐CAD‐QAMS approach. Some factors that affect the sensitivity and accuracy of the approach were sufficiently studied. After the method verification, principal component analysis (PCA) was applied to evaluate the quality consistency of three types of samples: normal samples, expired samples and negative samples. Results A HPLC‐CAD‐QAMS method was successfully developed for the multi‐component determination of QSYQ. First, chromatographic conditions were optimised by a definitive screening design, and the optimised ranges of operating parameters were obtained with a Monte Carlo simulation method. Next, a new method to select the internal reference standards was successfully introduced based on the heatmap of Pearson correlation coefficients of the response factors. Then, the multi‐point method was selected to calculate the relative correction factors, and a robustness test was conducted with Plackett–Burman design. Finally, the PCA was proved to be effective for the quality consistency evaluation of different samples. Conclusion The developed HPLC‐CAD‐QAMS method can be a reliable and superior means for the multi‐component quantitative analysis of QSYQ.